The application of relative navigation to civil air traffic management - Sangpetchsong, K (Cranfield University, 2000)
This thesis addresses navigation and guidance which will be required for air traffic management in Future Air Navigation Systems (FANS) and Free Flight. In particular, the thesis covers the issues of data fusion and integrity monitoring, to provide an adequate level of aircraft separation assurance, based on relative navigation (RELNAV). The evolution of air navigation systems is described. The principles of Kalman filtering and Joint Tactical Information Distribution System (JTIDS) RELNAV are covered. Sensor models of strapdown Inertial Navigation System (INS), Global Positioning System (GPS), and Automatic Dependent Surveillance-Broadcast (ADS-B) are developed in Matlab and integrated to form a hybrid navigation system. RELNAV algorithms for centralised and decentralised Kalman filtering are formulated, and their respective performances are analysed using Monte Carlo simulations for an airspace containing several aircraft. It is shown that RELNAV, based on the integration of INS and ADS-B, can enable aircraft to maintain safe separation independent of GPS, where it is assumed that an ADS-B datalink provides accurate time synchronisation. An alternative approach that integrates INS, GPS, and ADS-B is developed and analysed. It is shown that this approach is more applicable to civil aviation because it eliminates the needs to establish and manage several navigation communities simultaneously, in effect, exploiting GPS as the navigation controller. The source selection functions used for RELNAV are also developed, and the stability and performance of this technique is evaluated from simulation studies. A failure detection algorithm that monitors the residuals of a Kalman filter is derived and evaluated using Monte Carlo simulations of GPS failures. It is shown that this algorithm combines the use of likelihood functions and chi-squared tests, allowing both a false alarm rate to be selected and a failed sensor to be identified. Finally, an algorithm is developed for separation assurance to determine the probability that aircraft are closer than a pre-determined distance, taking into account flight path prediction errors. It is shown that this algorithm simplifies aircraft conflict detection in three dimensions and allows the conflict probability at a particular time to be determined. This approach is validated using Monte Carlo simulations of aircraft trajectories which include near-misses.